Accurately predicting environmental parameters in solar greenhouses is crucial for achieving precise environmental control.In solar greenhouses,temperature,humidity,and light intensity are crucial environmental parame...Accurately predicting environmental parameters in solar greenhouses is crucial for achieving precise environmental control.In solar greenhouses,temperature,humidity,and light intensity are crucial environmental parameters.The monitoring platform collected data on the internal environment of the solar greenhouse for one year,including temperature,humidity,and light intensity.Additionally,meteorological data,comprising outdoor temperature,outdoor humidity,and outdoor light intensity,was gathered during the same time frame.The characteristics and interrelationships among these parameters were investigated by a thorough analysis.The analysis revealed that environmental parameters in solar greenhouses displayed characteristics such as temporal variability,non-linearity,and periodicity.These parameters exhibited complex coupling relationships.Notably,these characteristics and coupling relationships exhibited pronounced seasonal variations.The multi-parameter multi-step prediction model for solar greenhouse(MPMS-SGH)was introduced,aiming to accurately predict three key greenhouse environmental parameters,and the model had certain seasonal adaptability.MPMS-SGH was structured with multiple layers,including an input layer,a preprocessing layer,a feature extraction layer,and a prediction layer.The input layer was used to generate the original sequence matrix,which included indoor temperature,indoor humidity,indoor light intensity,as well as outdoor temperature and outdoor light intensity.Then the preprocessing layer normalized,decomposed,and positionally encoded the original sequence matrix.In the feature extraction layer,the time attention mechanism and frequency attention mechanism were used to extract features from the trend component and the seasonal component,respectively.Finally,the prediction layer used a multi-layer perceptron to perform multi-step prediction of indoor environmental parameters(i.e.temperature,humidity,and light intensity).The parameter selection experiment evaluated the predictive performance of MPMS-SGH on input and output sequences of different lengths.The results indicated that with a constant output sequence length,the prediction accuracy of MPMS-SGH was firstly increased and then decreased with the increase of input sequence length.Specifically,when the input sequence length was 100,MPMS-SGH had the highest prediction accuracy,with RMSE of 0.22℃,0.28%,and 250lx for temperature,humidity,and light intensity,respectively.When the length of the input sequence remained constant,as the length of the output sequence increased,the accuracy of the model in predicting the three environmental parameters was continuously decreased.When the length of the output sequence exceeded 45,the prediction accuracy of MPMS-SGH was significantly decreased.In order to achieve the best balance between model size and performance,the input sequence length of MPMS-SGH was set to be 100,while the output sequence length was set to be 35.To assess MPMS-SGH’s performance,comparative experiments with four prediction models were conducted:SVR,STL-SVR,LSTM,and STL-LSTM.The results demonstrated that MPMS-SGH surpassed all other models,achieving RMSE of 0.15℃for temperature,0.38%for humidity,and 260lx for light intensity.Additionally,sequence decomposition can contribute to enhancing MPMS-SGH’s prediction performance.To further evaluate MPMS-SGH’s capabilities,its prediction accuracy was tested across different seasons for greenhouse environmental parameters.MPMS-SGH had the highest accuracy in predicting indoor temperature and the lowest accuracy in predicting humidity.And the accuracy of MPMS-SGH in predicting environmental parameters of the solar greenhouse fluctuated with seasons.MPMS-SGH had the highest accuracy in predicting the temperature inside the greenhouse on sunny days in spring(R^(2)=0.91),the highest accuracy in predicting the humidity inside the greenhouse on sunny days in winter(R^(2)=0.83),and the highest accuracy in predicting the light intensity inside the greenhouse on cloudy days in autumm(R^(2)=0.89).MPMS-SGH had the lowest accuracy in predicting three environmental parameters in a sunny summer greenhouse.展开更多
The advantage distillation(AD)technology has been proven to effectively improve the secret key rate and the communication distance of quantum key distribution(QKD).The mode-pairing quantum key distribution(MP-QKD)prot...The advantage distillation(AD)technology has been proven to effectively improve the secret key rate and the communication distance of quantum key distribution(QKD).The mode-pairing quantum key distribution(MP-QKD)protocol can overcome a fundamental physical limit,known as the Pirandola-Laurenza-Ottaviani-Banchi bound,without requiring global phase-locking.In this work,we propose a method based on multi-step AD to further enhance the performance of MP-QKD.The simulation results show that,compared to one-step AD,multi-step AD achieves better performance in long-distance scenarios and can tolerate a higher quantum bit error rate.Specifically,when the difference between the communication distances from Alice and Bob to Charlie is 25 km,50 km and 75 km,and the corresponding transmission distance exceeds 523 km,512 km and 496 km,respectively,the secret key rate achieved by multi-step AD surpasses that of one-step AD.Our findings indicate that the proposed method can effectively promote the application of MP-QKD in scenarios with high loss and high error rate.展开更多
In this paper,a composite numerical scheme is proposed to solve the threedimensional Darcy-Forchheimer miscible displacement problem with positive semi-definite assumptions.A mixed finite element is used for the fow e...In this paper,a composite numerical scheme is proposed to solve the threedimensional Darcy-Forchheimer miscible displacement problem with positive semi-definite assumptions.A mixed finite element is used for the fow equation.The velocity and pressure are computed simultaneously.The accuracy of velocity is improved one order.The concentration equation is solved by using mixed finite element,multi-step difference and upwind approximation.A multi-step method is used to approximate time derivative for improving the accuracy.The upwind approximation and an expanded mixed finite element are adopted to solve the convection and diffusion,respectively.The composite method could compute the diffusion flux and its gradient.It possibly becomes an eficient tool for solving convection-dominated diffusion problems.Firstly,the conservation of mass holds.Secondly,the multi-step method has high accuracy.Thirdly,the upwind approximation could avoid numerical dispersion.Using numerical analysis of a priori estimates and special techniques of differential equations,we give an error estimates for a positive definite problem.Numerical experiments illustrate its computational efficiency and feasibility of application.展开更多
随着全世界经济与网络时代的高速发展,电商物流这种新兴行业也繁荣起来。但我国大部分的物流企业采用的仍然是传统的成本核算法,这种方法会传递不实的成本信息、影响管理决策,让企业失去对成本的管理控制。而新兴的作业成本法则没有这...随着全世界经济与网络时代的高速发展,电商物流这种新兴行业也繁荣起来。但我国大部分的物流企业采用的仍然是传统的成本核算法,这种方法会传递不实的成本信息、影响管理决策,让企业失去对成本的管理控制。而新兴的作业成本法则没有这些缺点和不足,能够给企业提供更加真实准确的成本信息。基于以上背景,本文将充分利用前人已有的研究成果,以JD为案例,综合对比物流企业内成本核算的现状,建立作业成本法核算框架,探究作业成本法实际应用于物流企业的过程和可能带来的经济效益,最后针对其实施的过程提出改进建议,希望能达到优化JD作业成本管理方法的目标,同时也能为作业成本法在物流成本核算的应用方面提供科学的理论依据。With the rapid development of the world economy and the Internet era, the emerging industry of e-commerce logistics has also prospered. However, most of the logistics enterprises in our country still adopt the traditional cost accounting method, which will transmit false cost information, affect management decisions, and let enterprises lose the cost management control. The new activity-based costing method does not have these shortcomings and deficiencies, and can provide more real and accurate cost information for enterprises. Based on the above background, this paper will make full use of previous research achievements, take JD as a case, comprehensively compare the current situation of cost accounting in logistics enterprises, establish the accounting framework of activity-based costing, explore the actual application process of activity-based costing in logistics enterprises and the possible economic benefits, and finally put forward improvement suggestions for its implementation process. It is hoped that it can achieve the goal of optimizing JD activity-based costing management method and provide scientific theoretical basis for the application of activity-based costing in logistics cost accounting.展开更多
Acoustic holograms can recover wavefront stored acoustic field information and produce high-fidelity complex acoustic fields. Benefiting from the huge spatial information that traditional acoustic elements cannot matc...Acoustic holograms can recover wavefront stored acoustic field information and produce high-fidelity complex acoustic fields. Benefiting from the huge spatial information that traditional acoustic elements cannot match, acoustic holograms pursue the realization of high-resolution complex acoustic fields and gradually tend to high-frequency ultrasound applications. However, conventional continuous phase holograms are limited by three-dimensional(3D) printing size, and the presence of unavoidable small printing errors makes it difficult to achieve acoustic field reconstruction at high frequency accuracy. Here, we present an optimized discrete multi-step phase hologram. It can ensure the reconstruction quality of image with high robustness, and properly lower the requirement for the 3D printing accuracy. Meanwhile, the concept of reconstruction similarity is proposed to refine a measure of acoustic field quality. In addition, the realized complex acoustic field at 20 MHz promotes the application of acoustic holograms at high frequencies and provides a new way to generate high-fidelity acoustic fields.展开更多
以春光1号水稻为供试种子,链霉菌JD211为供试菌,通过浅盘试验研究链霉菌JD211对水稻生物量和土壤细菌多样性的影响。结果表明:菌剂用量10 g kg-1对水稻幼苗的生长有极显著的促进作用,幼苗总干重、地上部分干重、地下部分干重与对照相比...以春光1号水稻为供试种子,链霉菌JD211为供试菌,通过浅盘试验研究链霉菌JD211对水稻生物量和土壤细菌多样性的影响。结果表明:菌剂用量10 g kg-1对水稻幼苗的生长有极显著的促进作用,幼苗总干重、地上部分干重、地下部分干重与对照相比分别提高52.15%、44.56%、65.55%,植株全氮、全磷分别提高90.10%、58.51%。与CK土壤相比,菌剂用量10 g kg-1的土壤速效氮、有效磷均有显著提高,分别提高了37.49%、40.62%。细菌多样性的末端限制性片段长度多样性(T-RFLP)分析表明链霉菌JD211能促进一些稀有或生态势较弱的细菌生长,使参与土壤营养循环、改善土壤质地及防治植物病害的功能菌成为优势菌群。土壤功能微生物类群的变化,加速了N、P等土壤养分循环,增强了水稻对N、P等矿质养分的吸收,从而促进水稻生长。展开更多
文摘Accurately predicting environmental parameters in solar greenhouses is crucial for achieving precise environmental control.In solar greenhouses,temperature,humidity,and light intensity are crucial environmental parameters.The monitoring platform collected data on the internal environment of the solar greenhouse for one year,including temperature,humidity,and light intensity.Additionally,meteorological data,comprising outdoor temperature,outdoor humidity,and outdoor light intensity,was gathered during the same time frame.The characteristics and interrelationships among these parameters were investigated by a thorough analysis.The analysis revealed that environmental parameters in solar greenhouses displayed characteristics such as temporal variability,non-linearity,and periodicity.These parameters exhibited complex coupling relationships.Notably,these characteristics and coupling relationships exhibited pronounced seasonal variations.The multi-parameter multi-step prediction model for solar greenhouse(MPMS-SGH)was introduced,aiming to accurately predict three key greenhouse environmental parameters,and the model had certain seasonal adaptability.MPMS-SGH was structured with multiple layers,including an input layer,a preprocessing layer,a feature extraction layer,and a prediction layer.The input layer was used to generate the original sequence matrix,which included indoor temperature,indoor humidity,indoor light intensity,as well as outdoor temperature and outdoor light intensity.Then the preprocessing layer normalized,decomposed,and positionally encoded the original sequence matrix.In the feature extraction layer,the time attention mechanism and frequency attention mechanism were used to extract features from the trend component and the seasonal component,respectively.Finally,the prediction layer used a multi-layer perceptron to perform multi-step prediction of indoor environmental parameters(i.e.temperature,humidity,and light intensity).The parameter selection experiment evaluated the predictive performance of MPMS-SGH on input and output sequences of different lengths.The results indicated that with a constant output sequence length,the prediction accuracy of MPMS-SGH was firstly increased and then decreased with the increase of input sequence length.Specifically,when the input sequence length was 100,MPMS-SGH had the highest prediction accuracy,with RMSE of 0.22℃,0.28%,and 250lx for temperature,humidity,and light intensity,respectively.When the length of the input sequence remained constant,as the length of the output sequence increased,the accuracy of the model in predicting the three environmental parameters was continuously decreased.When the length of the output sequence exceeded 45,the prediction accuracy of MPMS-SGH was significantly decreased.In order to achieve the best balance between model size and performance,the input sequence length of MPMS-SGH was set to be 100,while the output sequence length was set to be 35.To assess MPMS-SGH’s performance,comparative experiments with four prediction models were conducted:SVR,STL-SVR,LSTM,and STL-LSTM.The results demonstrated that MPMS-SGH surpassed all other models,achieving RMSE of 0.15℃for temperature,0.38%for humidity,and 260lx for light intensity.Additionally,sequence decomposition can contribute to enhancing MPMS-SGH’s prediction performance.To further evaluate MPMS-SGH’s capabilities,its prediction accuracy was tested across different seasons for greenhouse environmental parameters.MPMS-SGH had the highest accuracy in predicting indoor temperature and the lowest accuracy in predicting humidity.And the accuracy of MPMS-SGH in predicting environmental parameters of the solar greenhouse fluctuated with seasons.MPMS-SGH had the highest accuracy in predicting the temperature inside the greenhouse on sunny days in spring(R^(2)=0.91),the highest accuracy in predicting the humidity inside the greenhouse on sunny days in winter(R^(2)=0.83),and the highest accuracy in predicting the light intensity inside the greenhouse on cloudy days in autumm(R^(2)=0.89).MPMS-SGH had the lowest accuracy in predicting three environmental parameters in a sunny summer greenhouse.
基金supported by the National Natural Science Foundation of China(Grant Nos.62171144and 62031024)Guangxi Science Foundation(Grant Nos.2025GXNSFAA069137 and GXR-1BGQ2424005)Innovation Project of Guangxi Graduate Education(Grant No.YCBZ2025064)。
文摘The advantage distillation(AD)technology has been proven to effectively improve the secret key rate and the communication distance of quantum key distribution(QKD).The mode-pairing quantum key distribution(MP-QKD)protocol can overcome a fundamental physical limit,known as the Pirandola-Laurenza-Ottaviani-Banchi bound,without requiring global phase-locking.In this work,we propose a method based on multi-step AD to further enhance the performance of MP-QKD.The simulation results show that,compared to one-step AD,multi-step AD achieves better performance in long-distance scenarios and can tolerate a higher quantum bit error rate.Specifically,when the difference between the communication distances from Alice and Bob to Charlie is 25 km,50 km and 75 km,and the corresponding transmission distance exceeds 523 km,512 km and 496 km,respectively,the secret key rate achieved by multi-step AD surpasses that of one-step AD.Our findings indicate that the proposed method can effectively promote the application of MP-QKD in scenarios with high loss and high error rate.
基金supported by the Natural Science Foundation of Shandong Province(ZR2021MA019)the National Natural Science Foundation of China(11871312)。
文摘In this paper,a composite numerical scheme is proposed to solve the threedimensional Darcy-Forchheimer miscible displacement problem with positive semi-definite assumptions.A mixed finite element is used for the fow equation.The velocity and pressure are computed simultaneously.The accuracy of velocity is improved one order.The concentration equation is solved by using mixed finite element,multi-step difference and upwind approximation.A multi-step method is used to approximate time derivative for improving the accuracy.The upwind approximation and an expanded mixed finite element are adopted to solve the convection and diffusion,respectively.The composite method could compute the diffusion flux and its gradient.It possibly becomes an eficient tool for solving convection-dominated diffusion problems.Firstly,the conservation of mass holds.Secondly,the multi-step method has high accuracy.Thirdly,the upwind approximation could avoid numerical dispersion.Using numerical analysis of a priori estimates and special techniques of differential equations,we give an error estimates for a positive definite problem.Numerical experiments illustrate its computational efficiency and feasibility of application.
文摘随着全世界经济与网络时代的高速发展,电商物流这种新兴行业也繁荣起来。但我国大部分的物流企业采用的仍然是传统的成本核算法,这种方法会传递不实的成本信息、影响管理决策,让企业失去对成本的管理控制。而新兴的作业成本法则没有这些缺点和不足,能够给企业提供更加真实准确的成本信息。基于以上背景,本文将充分利用前人已有的研究成果,以JD为案例,综合对比物流企业内成本核算的现状,建立作业成本法核算框架,探究作业成本法实际应用于物流企业的过程和可能带来的经济效益,最后针对其实施的过程提出改进建议,希望能达到优化JD作业成本管理方法的目标,同时也能为作业成本法在物流成本核算的应用方面提供科学的理论依据。With the rapid development of the world economy and the Internet era, the emerging industry of e-commerce logistics has also prospered. However, most of the logistics enterprises in our country still adopt the traditional cost accounting method, which will transmit false cost information, affect management decisions, and let enterprises lose the cost management control. The new activity-based costing method does not have these shortcomings and deficiencies, and can provide more real and accurate cost information for enterprises. Based on the above background, this paper will make full use of previous research achievements, take JD as a case, comprehensively compare the current situation of cost accounting in logistics enterprises, establish the accounting framework of activity-based costing, explore the actual application process of activity-based costing in logistics enterprises and the possible economic benefits, and finally put forward improvement suggestions for its implementation process. It is hoped that it can achieve the goal of optimizing JD activity-based costing management method and provide scientific theoretical basis for the application of activity-based costing in logistics cost accounting.
基金Project supported by the China Postdoctoral Science Foundation (Grant No.2023M732745)the National Natural Science Foundations of China (Grant Nos.61974110 and 62104177)+1 种基金the Fundamental Research Funds for the Central Universities,China (Grant Nos.QTZX23022 and JBF211103)the Cooperation Program of XDU– Chongqing IC Innovation Research Institute (Grant No.CQ IRI-2022CXY-Z07)。
文摘Acoustic holograms can recover wavefront stored acoustic field information and produce high-fidelity complex acoustic fields. Benefiting from the huge spatial information that traditional acoustic elements cannot match, acoustic holograms pursue the realization of high-resolution complex acoustic fields and gradually tend to high-frequency ultrasound applications. However, conventional continuous phase holograms are limited by three-dimensional(3D) printing size, and the presence of unavoidable small printing errors makes it difficult to achieve acoustic field reconstruction at high frequency accuracy. Here, we present an optimized discrete multi-step phase hologram. It can ensure the reconstruction quality of image with high robustness, and properly lower the requirement for the 3D printing accuracy. Meanwhile, the concept of reconstruction similarity is proposed to refine a measure of acoustic field quality. In addition, the realized complex acoustic field at 20 MHz promotes the application of acoustic holograms at high frequencies and provides a new way to generate high-fidelity acoustic fields.
文摘以春光1号水稻为供试种子,链霉菌JD211为供试菌,通过浅盘试验研究链霉菌JD211对水稻生物量和土壤细菌多样性的影响。结果表明:菌剂用量10 g kg-1对水稻幼苗的生长有极显著的促进作用,幼苗总干重、地上部分干重、地下部分干重与对照相比分别提高52.15%、44.56%、65.55%,植株全氮、全磷分别提高90.10%、58.51%。与CK土壤相比,菌剂用量10 g kg-1的土壤速效氮、有效磷均有显著提高,分别提高了37.49%、40.62%。细菌多样性的末端限制性片段长度多样性(T-RFLP)分析表明链霉菌JD211能促进一些稀有或生态势较弱的细菌生长,使参与土壤营养循环、改善土壤质地及防治植物病害的功能菌成为优势菌群。土壤功能微生物类群的变化,加速了N、P等土壤养分循环,增强了水稻对N、P等矿质养分的吸收,从而促进水稻生长。
